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Privacy Preserving on Trajectories Created by Wi-Fi Connections in a University Campus

机译:在大学校园中通过Wi-Fi连接创建的轨迹的隐私保护

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In universities, it is common to find many access points widely distributed through the campus aiming to cover most of the area with Wi-Fi signal. Each time a connection between a device and an access point is performed, the data generated by that action (e.g., location, student identification and time) are stored in a log file. This file allow us to track back the trajectories of the students inside the universities, ordering this data by time. With the identification attribute of the student, it is possible to join it with quasi-identifiers present in the university systems. Publication of such data may put the privacy of university students in risk. Given that, this article proposes a method of anonymization called Mix β-k-anonymity. This technique provides a set of possible trajectories of a group of people with the same quasi-identifiers. After the application of this method, it is showed that with the right choice of the quasi-identifier is possible to anonymize the trajectories making possible the disclosure for operational mobility research on campus.
机译:在大学中,通常会找到许多遍布校园的接入点,这些接入点旨在通过Wi-Fi信号覆盖大部分区域。每次执行设备与接入点之间的连接时,由该操作生成的数据(例如位置,学生身份和时间)都存储在日志文件中。该文件使我们可以追溯大学内部学生的轨迹,并按时间排序该数据。利用学生的识别属性,可以将其与大学系统中存在的准标识符一起加入。此类数据的发布可能会使大学生的隐私受到威胁。鉴于此,本文提出了一种称为Mixβ-k-anonymity的匿名方法。该技术提供了一组具有相同准标识符的人的可能轨迹。应用该方法后,结果表明,通过正确选择准标识符,可以对轨迹进行匿名处理,从而可以公开进行校园运营移动性研究。

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